Digital video signals may be obtained by transducing a light pattern (electromagnetic waves, for example, in the visual spectrum) into an analogue video signal using an imaging device and subsequently obtaining a digital representation of the analogue video signal by sampling.
Prediction coding methods can be used for coding sequences of video frames. By such methods, a given frame can be expressed in terms of its difference with respect to one or more of the preceding frames. This idea can be applied to many image formats such as formats based on harmonic transforms or the discrete cosine transform (DCT) and its variants. Prediction coding can exploit the correlation between consecutive frames that is inherent in realistic video data so as to provide a low-bitrate coding format. In some instances, this efficiency, however, is achieved at a certain cost: a prediction-coded video sequence may only be decoded sequentially. In other words, the prediction-coded sequence may only be decoded in the same order as it was encoded so that frames preceding the one to be decoded are known. Further, in some instances, prediction decoders may not be able to skip forward in the video sequence and omit one or more frames whilst maintaining error-free decoding. Put differently, the decoder is a state-dependent (or stateful or memoryful) device, and the way it processes information relating to a given frame can depend on the previously decoded frame(s).
Transmission services over Internet Protocol (IP) networks can be supplied on a best-effort basis. A best-effort basis can include no guarantees as to whether a data packet will reach its addressee or how soon. When prediction-coded video frames are supplied in real time over an IP network, it may happen that a video frame is lost, is delivered incomplete or contains errors. The decoding process may not be able to continue in an error-free manner until the frame has been restored.